Radiotherapy of Skeletal Metastases
Bibliographic record
Abstract
INTRODUCTION: Patients with skeletal metastases represent a large cohort in clinical oncology, and the single most frequent indication for palliative radiotherapy. Patients with cancer of the breast, lung, prostate and those with myelomatosis, constitute approximately 80% of this group. MATERIAL AND METHODS: This paper summarizes data from relevant published clinical trials employing external irradiation for painful skeletal metastases. More recent randomised trials support the view that a single radiation dose of 8-10 Gy is equally efficient as ten treatments of 3 Gy delivered over two weeks. However, some still believe that fractioned regimes to a higher total dose provide better pain relief of a longer duration than a single fraction. RESULTS: We review the current diagnosis and treatment of patients with skeletal metastases and discuss some aspect of tumour biology. The etiology of pain and the pathogenesis of tumour cells affecting bone tissue, resulting in osteolysis and/or osteosclerosis, are discussed. Associated leukocyte-derived osteoclast-activating cytokines that stimulate pain receptors locally, can in part explain why radiotherapy gives such rapid pain relief. INTERPRETATION: The aims of radiotherapy must be assessed in relation to the life expectancy of the patient. Based on actual publications and own experiences, we suggest treatment with 8 Gy x 1 for the majority of patients, and reserve 3 Gy x 10 for patients with longer life expectancy. Both regimes allow retreatment, if and when pain eventually reoccur in previously irradiated areas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".